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Record W3184747793 · doi:10.5539/ibr.v14n8p55

An Evaluation of Tourism Attributes related to Satisfaction and Challenges by Foreign Tourists in Sultanate of Oman

2021· article· en· W3184747793 on OpenAlexvenueno aff
Renjith Kumar R., Ruwaiya Salim Said Al Shekaili, Bahia Dawood Sulaiman Al-Sulaimi, Rahma Khalid Sulaiman Al-Alawi

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
FundersMinistry of Higher Education, Research and Innovation
KeywordsTourismOpenness to experienceBusinessTicketMarketingDestinationsFeelingGeographyPsychology

Abstract

fetched live from OpenAlex

Tourism economy has enhanced the employment opportunities in Oman and lot of new tourism projects are coming up throughout the country. The awareness among the Omani public has to improve to consider a future in the tourism industry. The study is attempted to understand the satisfaction level of international tourists in Oman, the factors that affects tourism and the challenges faced by the tourists. The responses were collected from 111 foreign tourists visited Oman. It was found that majority of the tourists are from France, Germany, Italy and Britain. International tourists are satisfied by the friendliness and openness of Omanis, culture and customs and have a safe feeling of security to travel in Oman. The challenges faced by foreign tourists include difficulty in language, GPS connection, lack of Wifi connectivity, problems in walking alone, more time at the airport to exit, time for visa processing, bad driving, expensive ticket charges, taxi and hotel charges, crowded and traffic jam and language difficulties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.085
GPT teacher head0.366
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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